Drone thermal imaging for assessing water status response of variable nitrogen and water application in wheat

Efficient water and nitrogen management is crucial for improving wheat productivity, especially under limited resource conditions and remote sensing through drone has emerged as an efficient tool for real-time, large scale crop monitoring. This study examines the application of drone-mounted thermal sensor to assess water stress by measuring canopy temperature, relative leaf water content (RWC), stomatal conductance (GS) and transpiration rate (Tr), key indicators of crop water status. The finding demonstrate that both irrigation and nitrogen levels substantially influence these physiological parameters, with irrigation effectively lowering canopy temperature and Simplified Crop Water Stress Index (CWSIsi) values. Canopy temperature derived through NDVI co-registration method showed robust correlation with ground-truth data (R2 = 0.92). Derived from thermal imagery, the CWSIsi correlated well with RWC (R2 = 0.73), Gs (R2 = 0.63), and Tr (R2 = 0.73) during the reproductive stage. Strong negative correlations were observed between CWSIsi and parameters like soil moisture (r = - 0.748**), RWC (r = - 0.855**), Gs (r = - 0.793**), Tr (r = - 0.857**), and grain yield (r = - 0.846**). These findings support the viability of drone-based thermal sensing for large-scale, real-time monitoring of water stress, aiding in the effective management of water and nitrogen resources to maximize wheat yield.